Bernard, Jürgen ; Hutter, Marco ; Sessler, David ; Schreck, Tobias ; Behrisch, Michael ; Kohlhammer, Jörn (2014)
Towards a User-Defined Visual-Interactive Definition of Similarity Functions for Mixed Data.
IEEE Conference on Visual Analytics Science and Technology. Proceedings.
doi: 10.1109/VAST.2014.7042503
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
The creation of similarity functions based on visual-interactive user feedback is a promising means to capture the mental similarity notion in the heads of domain experts. In particular, concepts exist where users arrange multivariate data objects on a 2D data landscape in order to learn new similarity functions. While systems that incorporate numerical data attributes have been presented in the past, the remaining overall goal may be to develop systems also for mixed data sets. In this work, we present a feedback model for categorical data which can be used alongside of numerical feedback models in future.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2014 |
| Autor(en): | Bernard, Jürgen ; Hutter, Marco ; Sessler, David ; Schreck, Tobias ; Behrisch, Michael ; Kohlhammer, Jörn |
| Art des Eintrags: | Bibliographie |
| Titel: | Towards a User-Defined Visual-Interactive Definition of Similarity Functions for Mixed Data |
| Sprache: | Englisch |
| Publikationsjahr: | 2014 |
| Verlag: | IEEE Computer Society, Los Alamitos, Calif. |
| Veranstaltungstitel: | IEEE Conference on Visual Analytics Science and Technology. Proceedings |
| DOI: | 10.1109/VAST.2014.7042503 |
| Kurzbeschreibung (Abstract): | The creation of similarity functions based on visual-interactive user feedback is a promising means to capture the mental similarity notion in the heads of domain experts. In particular, concepts exist where users arrange multivariate data objects on a 2D data landscape in order to learn new similarity functions. While systems that incorporate numerical data attributes have been presented in the past, the remaining overall goal may be to develop systems also for mixed data sets. In this work, we present a feedback model for categorical data which can be used alongside of numerical feedback models in future. |
| Freie Schlagworte: | Business Field: Visual decision support, Business Field: Digital society, Research Area: Computer vision (CV), Research Area: Human computer interaction (HCI), Visual analytics, Information visualization, Similarity measures, Similarity metrics, Similarity search |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Graphisch-Interaktive Systeme |
| Hinterlegungsdatum: | 12 Nov 2018 11:16 |
| Letzte Änderung: | 12 Nov 2018 11:16 |
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